Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
LargeRDFBench
1. Muhammad Saleem , Ali Hasnai, Axel-Cyrille Ngonga Ngomo
AKSW, University of Leipzig, Germany
DICE, University of Paderborn,
Germany
INSIGHT, University of Galway, Ireland
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2. Federated Benchmark Design Features
Why LargeRDFBench?
Evaluation and results
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4. Datasets used in the federation benchmark should vary:
Number of triples
Number of classes
Number of resources
Number of properties
Number of objects
Average properties per class
Average instances per class
Average in-degree and out-degree
Structuredness or coherence
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5. Number of triple patterns
Number of join vertices
Mean join vertex degree,
Number of sources span
Query result set sizes
Mean triple pattern selectivity
BGP-restricted triple pattern selectivity
Join-restricted triple pattern selectivity
Join vertex types (`star', `path', `hybrid', `sink')
SPARQL clauses used (e.g., LIMIT, UNION, OPTIONAL, FILTER
etc.) 5
6. Result set completeness and correctness
Number of sources selected
Number of SPARQL ASK requests used during source selection
Source selection time
Number of endpoint requests
Number of intermediate results
Overall query execution time
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7. SPARQL query federation benchmark
13 interconnect real datasets
4 Life sciences
6 Cross domain
3 Large data
40 queries of varying complexities
14 simple (from FedBench)
10 complex
8 large data
8 complex plus high data sources
Multiple performance metrics
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23. 23
FedX(Warm) SPLENDID ANAPSID FedX+HiBISCuS SPLENDID+HiBISCuS
#Triple Patterns 0.537 0.453 0.621 0.492
#Sources Span 0.233 0.232 0.245 0.019 0.290
#Results 0.583 0.553 0.085 0.534 0.476
#Join Vertices 0.275 0.289 0.214 0.301 0.284
Mean Join Vertex Degree 0.500 0.210 0.226 0.382 0.183
Mean TP Selectivity 0.261 0.304 0.198 0.237 0.263
Mean BGP-restricted TP Sel -0.065 -0.022 -0.190 -0.014 -0.042
Mean Join-restricted TP Sel 0.654 -0.334 -0.224 -0.472 -0.441
Results are significant at 1% level
Results are significant at 5% level
Results are significant at 10% level
Most influential Features
# Triple Pattern Result size Join-restricted TP selectivity
Number of join vertices Mean Join vertex degree Mean
TP selectivity Number of sources span BGP-restricted TP
selectivity
24. Simple queries benchmarks are not sufficient to perform a fair
comparison of federation engines
Positioning of federation engines greatly changes from Simple to
Complex queries
Federation engines are unstable when exposed to Large Data or
Complex + High Sources queries
Number of triple patterns, Result Size, and Join-restricted TP
selectivity are the three most influential query features
Smaller number of endpoints requests does not necessary mean
smaller execution time
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25. This work was supported by grants from the EU H2020 Framework Programme
provided for the project HOBBIT (GA no. 688227).